By using data analytics, Parkview Medical Center and Pieces Technology addressed social determinants of health and decreased their average length of stay rates among patients.
Parkview Medical Center...
To effectively document the severity of patient conditions and use risk stratification, the Community Health Network (CHN) in Indiana has streamlined hierarchical condition category (HCC) coding to...
When applied to a clinical data registry, machine learning algorithms showed no significant improvement in predicting adverse outcomes after an acute myocardial infarction (AMI), a study published in...
Researchers at the Perelman School of Medicine at the University of Pennsylvania have designed a new kind of patient data registry to advance rare disease research.
In a paper published in Cell...
A lack of national standards for social determinants of health quality metrics impedes progress, but a plan for setting nationwide guidelines could be the first step to nationally addressing these...
Data access and industry standards may help leaders eliminate potential bias in healthcare artificial intelligence tools, as well as improve implementation of the technology, according to a report from...
More robust and standardized social determinants of health (SDOH) data will improve SDOH initiatives and patient care, according to providers in Insights by Xtelligent Healthcare Media’s most...
The majority of COVID-19 data visualizations shared by average Twitter users contained one of five errors that reduced their accuracy or reliability, according to a study published in Informatics.
For...
Policymakers in Wisconsin have developed a ten-year plan to reduce cancer care disparities by improving data quality and expanding access to genetic testing.
Created by the Wisconsin Care...
A team from Stevens Institute of Technology has developed an artificial intelligence tool that can diagnose Alzheimer’s disease with more than 95 percent accuracy, eliminating the need for...
Decision-makers should take several criteria into account when assessing the usefulness of COVID-19 data points, according to a new guide by the National Academies of Sciences, Engineering and...
When one considers the healthcare industry, it’s easy to picture the entire ecosystem existing as one massive, cohesive machine – a system seamlessly working to achieve the goals of quality care, lower costs, and improved...
When evaluating COVID-19 data to inform policies, decision-makers should consider five criteria to better understand the spread of the virus in their communities: representativeness, potential...
A team from Regenstrief Institute and the Indiana University School of Medicine is applying data analytics techniques to previously inaccessible dental record information with the goal of improving...
At Southern Illinois Healthcare and Care New England, internal data and analytics has empowered the organizations and pushed the quality improvement programs forward.
These programs are contingent on...
COVID-19 data gathered during the pandemic has shed light on significant healthcare disparities, revealing poorer outcomes in minority and underserved communities.
For more coronavirus updates, visit...
The Radiological Society of North America (RSNA) has created a public medical imaging dataset of expert-annotated brain hemorrhage CT scans, leading to the development of machine learning algorithms...
Before the world was even conscious of the threat posed by COVID-19, artificial intelligence had detected the beginnings of the outbreak.
For more coronavirus updates, visit our resource page, updated...
Across the healthcare landscape, it is now widely understood that the social determinants of health (SDOH) have a major impact on health outcomes, care quality, and medical costs.
An...
Hospitals and health information exchanges (HIEs) still struggle with patient matching issues, with many citing data quality problems and poor algorithms as top barriers to patient matching, according...